Overview

Dataset statistics

Number of variables28
Number of observations37813
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 MiB
Average record size in memory224.0 B

Variable types

NUM15
CAT8
BOOL5

Warnings

total_land_area is highly correlated with garden_areaHigh correlation
garden_area is highly correlated with total_land_areaHigh correlation
subtype_of_property is highly correlated with type_of_property and 1 other fieldsHigh correlation
type_of_property is highly correlated with subtype_of_property and 1 other fieldsHigh correlation
province is highly correlated with region and 1 other fieldsHigh correlation
region is highly correlated with province and 1 other fieldsHigh correlation
type_of_property_num is highly correlated with type_of_property and 1 other fieldsHigh correlation
region_num is highly correlated with region and 1 other fieldsHigh correlation
area is highly skewed (γ1 = 21.46038373) Skewed
terrace_area is highly skewed (γ1 = 113.1304659) Skewed
garden_area is highly skewed (γ1 = 88.06374136) Skewed
total_land_area is highly skewed (γ1 = 84.15953068) Skewed
id has unique values Unique
nr_of_rooms has 730 (1.9%) zeros Zeros
garden_area has 20370 (53.9%) zeros Zeros

Reproduction

Analysis started2020-12-07 05:39:24.812530
Analysis finished2020-12-07 05:40:37.167878
Duration1 minute and 12.36 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

id
Real number (ℝ≥0)

UNIQUE

Distinct37813
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8852120.03
Minimum1882546
Maximum9066628
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:37.458278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1882546
5-th percentile8271417.6
Q18825271
median8954685
Q39020304
95-th percentile9057871.4
Maximum9066628
Range7184082
Interquartile range (IQR)195033

Descriptive statistics

Standard deviation327088.2773
Coefficient of variation (CV)0.03695027588
Kurtosis50.31477971
Mean8852120.03
Median Absolute Deviation (MAD)79521
Skewness-5.19368627
Sum3.347252147e+11
Variance1.069867411e+11
MonotocityNot monotonic
2020-12-07T06:40:37.784008image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
89390451< 0.1%
 
89577541< 0.1%
 
89245591< 0.1%
 
89880461< 0.1%
 
90576761< 0.1%
 
90231841< 0.1%
 
90105651< 0.1%
 
82665351< 0.1%
 
90638111< 0.1%
 
89306901< 0.1%
 
Other values (37803)37803> 99.9%
 
ValueCountFrequency (%) 
18825461< 0.1%
 
23357391< 0.1%
 
27849381< 0.1%
 
30011351< 0.1%
 
37945241< 0.1%
 
ValueCountFrequency (%) 
90666281< 0.1%
 
90665561< 0.1%
 
90665271< 0.1%
 
90664171< 0.1%
 
90663991< 0.1%
 

locality
Real number (ℝ≥0)

Distinct1014
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5138.92127
Minimum1000
Maximum9992
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:38.108049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1000
5-th percentile1070
Q12100
median4671
Q38400
95-th percentile9500
Maximum9992
Range8992
Interquartile range (IQR)6300

Descriptive statistics

Standard deviation3118.850063
Coefficient of variation (CV)0.6069075393
Kurtosis-1.618424221
Mean5138.92127
Median Absolute Deviation (MAD)3112
Skewness0.08205409166
Sum194318030
Variance9727225.715
MonotocityNot monotonic
2020-12-07T06:40:38.418670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
830010512.8%
 
11807281.9%
 
10006431.7%
 
84005811.5%
 
90005381.4%
 
20004741.3%
 
10504431.2%
 
83704151.1%
 
10704061.1%
 
86703430.9%
 
Other values (1004)3219185.1%
 
ValueCountFrequency (%) 
10006431.7%
 
10201250.3%
 
10303240.9%
 
10401520.4%
 
10504431.2%
 
ValueCountFrequency (%) 
99923< 0.1%
 
9991690.2%
 
9990620.2%
 
99889< 0.1%
 
99824< 0.1%
 

type_of_property
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
APARTMENT
20229 
HOUSE
17584 
ValueCountFrequency (%) 
APARTMENT2022953.5%
 
HOUSE1758446.5%
 
2020-12-07T06:40:38.680051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-07T06:40:38.808682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:38.983478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length9
Mean length7.139898977
Min length5

subtype_of_property
Categorical

HIGH CORRELATION

Distinct22
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
APARTMENT
15399 
HOUSE
12906 
VILLA
2594 
DUPLEX
 
1306
GROUND_FLOOR
 
1109
Other values (17)
4499 
ValueCountFrequency (%) 
APARTMENT1539940.7%
 
HOUSE1290634.1%
 
VILLA25946.9%
 
DUPLEX13063.5%
 
GROUND_FLOOR11092.9%
 
PENTHOUSE9702.6%
 
FLAT_STUDIO7201.9%
 
MIXED_USE_BUILDING4461.2%
 
EXCEPTIONAL_PROPERTY4281.1%
 
SERVICE_FLAT3200.8%
 
Other values (12)16154.3%
 
2020-12-07T06:40:39.231178image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-07T06:40:39.482184image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length20
Median length9
Mean length7.617671171
Min length3

price
Real number (ℝ≥0)

Distinct3591
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean393353.9229
Minimum2500
Maximum9500000
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:39.709587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2500
5-th percentile125000
Q1209500
median285000
Q3409825
95-th percentile995000
Maximum9500000
Range9497500
Interquartile range (IQR)200325

Descriptive statistics

Standard deviation419522.594
Coefficient of variation (CV)1.066527037
Kurtosis53.08026823
Mean393353.9229
Median Absolute Deviation (MAD)90280
Skewness5.704647086
Sum1.487389189e+10
Variance1.759992069e+11
MonotocityNot monotonic
2020-12-07T06:40:39.999347image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2490005141.4%
 
2990004811.3%
 
1990004761.3%
 
2750004611.2%
 
2950004411.2%
 
2250004081.1%
 
3950003871.0%
 
2350003811.0%
 
1950003811.0%
 
1750003801.0%
 
Other values (3581)3350388.6%
 
ValueCountFrequency (%) 
25003< 0.1%
 
40001< 0.1%
 
99991< 0.1%
 
100003< 0.1%
 
118251< 0.1%
 
ValueCountFrequency (%) 
95000001< 0.1%
 
87500001< 0.1%
 
85000001< 0.1%
 
77500001< 0.1%
 
65000004< 0.1%
 

nr_of_rooms
Real number (ℝ≥0)

ZEROS

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.740221617
Minimum0
Maximum18
Zeros730
Zeros (%)1.9%
Memory size295.4 KiB
2020-12-07T06:40:40.237899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum18
Range18
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.350243159
Coefficient of variation (CV)0.4927496195
Kurtosis7.135375623
Mean2.740221617
Median Absolute Deviation (MAD)1
Skewness1.497759931
Sum103616
Variance1.823156589
MonotocityNot monotonic
2020-12-07T06:40:40.404033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
21272233.6%
 
31210832.0%
 
4484012.8%
 
1424811.2%
 
519315.1%
 
07301.9%
 
67141.9%
 
72410.6%
 
81290.3%
 
9540.1%
 
Other values (5)960.3%
 
ValueCountFrequency (%) 
07301.9%
 
1424811.2%
 
21272233.6%
 
31210832.0%
 
4484012.8%
 
ValueCountFrequency (%) 
185< 0.1%
 
156< 0.1%
 
12230.1%
 
11200.1%
 
10420.1%
 

area
Real number (ℝ≥0)

SKEWED

Distinct737
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean159.1854918
Minimum5
Maximum11366
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:40.639591image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile55
Q190
median125
Q3185
95-th percentile375
Maximum11366
Range11361
Interquartile range (IQR)95

Descriptive statistics

Standard deviation146.335724
Coefficient of variation (CV)0.9192780218
Kurtosis1290.644734
Mean159.1854918
Median Absolute Deviation (MAD)42
Skewness21.46038373
Sum6019281
Variance21414.14411
MonotocityNot monotonic
2020-12-07T06:40:41.014904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
908122.1%
 
1008102.1%
 
1207151.9%
 
806721.8%
 
1106491.7%
 
1506311.7%
 
856131.6%
 
1405921.6%
 
705461.4%
 
2005411.4%
 
Other values (727)3123282.6%
 
ValueCountFrequency (%) 
51< 0.1%
 
131< 0.1%
 
141< 0.1%
 
152< 0.1%
 
167< 0.1%
 
ValueCountFrequency (%) 
113661< 0.1%
 
87501< 0.1%
 
43801< 0.1%
 
40001< 0.1%
 
35003< 0.1%
 

equiped_kitchen
Categorical

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
INSTALLED
13832 
UNK
11324 
HYPER_EQUIPPED
5778 
SEMI_EQUIPPED
2617 
USA_HYPER_EQUIPPED
1921 
Other values (4)
2341 
ValueCountFrequency (%) 
INSTALLED1383236.6%
 
UNK1132429.9%
 
HYPER_EQUIPPED577815.3%
 
SEMI_EQUIPPED26176.9%
 
USA_HYPER_EQUIPPED19215.1%
 
NOT_INSTALLED14363.8%
 
USA_INSTALLED7261.9%
 
USA_SEMI_EQUIPPED1590.4%
 
USA_UNINSTALLED200.1%
 
2020-12-07T06:40:41.269699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-07T06:40:41.472668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:41.740682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length9
Mean length8.966757464
Min length3

open_fire
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
0
35747 
1
 
2066
ValueCountFrequency (%) 
03574794.5%
 
120665.5%
 
2020-12-07T06:40:41.888364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

terrace
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
1
24075 
0
13738 
ValueCountFrequency (%) 
12407563.7%
 
01373836.3%
 
2020-12-07T06:40:41.959849image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

terrace_area
Real number (ℝ)

SKEWED

Distinct208
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.4556105
Minimum-1
Maximum20000
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:42.145231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median-1
Q312
95-th percentile50
Maximum20000
Range20001
Interquartile range (IQR)13

Descriptive statistics

Standard deviation129.897641
Coefficient of variation (CV)11.33921592
Kurtosis15747.18542
Mean11.4556105
Median Absolute Deviation (MAD)0
Skewness113.1304659
Sum433171
Variance16873.39714
MonotocityNot monotonic
2020-12-07T06:40:42.397990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
-12234159.1%
 
108772.3%
 
208382.2%
 
67241.9%
 
156781.8%
 
126621.8%
 
86601.7%
 
305791.5%
 
95401.4%
 
55201.4%
 
Other values (198)939424.8%
 
ValueCountFrequency (%) 
-12234159.1%
 
1670.2%
 
23000.8%
 
33560.9%
 
45101.3%
 
ValueCountFrequency (%) 
200001< 0.1%
 
80002< 0.1%
 
60001< 0.1%
 
35001< 0.1%
 
34001< 0.1%
 

garden
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
0
19037 
1
18776 
ValueCountFrequency (%) 
01903750.3%
 
11877649.7%
 
2020-12-07T06:40:43.041682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

garden_area
Real number (ℝ)

HIGH CORRELATION
SKEWED
ZEROS

Distinct2943
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean683.1153043
Minimum-1
Maximum1134500
Zeros20370
Zeros (%)53.9%
Memory size295.4 KiB
2020-12-07T06:40:43.221427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile0
Q10
median0
Q3280
95-th percentile2000
Maximum1134500
Range1134501
Interquartile range (IQR)280

Descriptive statistics

Standard deviation8745.473068
Coefficient of variation (CV)12.80233807
Kurtosis10017.43051
Mean683.1153043
Median Absolute Deviation (MAD)0
Skewness88.06374136
Sum25830639
Variance76483299.18
MonotocityNot monotonic
2020-12-07T06:40:43.488386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
02037053.9%
 
1002420.6%
 
2001920.5%
 
501670.4%
 
3001530.4%
 
-11360.4%
 
4001330.4%
 
1501330.4%
 
601300.3%
 
801280.3%
 
Other values (2933)1602942.4%
 
ValueCountFrequency (%) 
-11360.4%
 
02037053.9%
 
1750.2%
 
2240.1%
 
3260.1%
 
ValueCountFrequency (%) 
11345001< 0.1%
 
8494501< 0.1%
 
3958501< 0.1%
 
3126001< 0.1%
 
2487001< 0.1%
 

total_land_area
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED

Distinct3201
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean883.6929892
Minimum5
Maximum1135150
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:43.739502image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile60
Q1100
median170
Q3482
95-th percentile2401.2
Maximum1135150
Range1135145
Interquartile range (IQR)382

Descriptive statistics

Standard deviation8900.922236
Coefficient of variation (CV)10.07241468
Kurtosis9361.911167
Mean883.6929892
Median Absolute Deviation (MAD)92
Skewness84.15953068
Sum33415083
Variance79226416.65
MonotocityNot monotonic
2020-12-07T06:40:43.972872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
904551.2%
 
1004521.2%
 
804131.1%
 
1103791.0%
 
953681.0%
 
1203661.0%
 
853410.9%
 
703230.9%
 
753140.8%
 
1053020.8%
 
Other values (3191)3410090.2%
 
ValueCountFrequency (%) 
51< 0.1%
 
131< 0.1%
 
141< 0.1%
 
152< 0.1%
 
167< 0.1%
 
ValueCountFrequency (%) 
11351501< 0.1%
 
8500001< 0.1%
 
3963001< 0.1%
 
3128411< 0.1%
 
2500001< 0.1%
 

nr_of_facades
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.729140772
Minimum-1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:44.174633image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median2
Q33
95-th percentile4
Maximum10
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.875176636
Coefficient of variation (CV)1.084455741
Kurtosis-1.220394999
Mean1.729140772
Median Absolute Deviation (MAD)1
Skewness-0.4486850723
Sum65384
Variance3.516287416
MonotocityNot monotonic
2020-12-07T06:40:44.325424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
21231332.6%
 
-11078228.5%
 
4796621.1%
 
3645517.1%
 
12950.8%
 
101< 0.1%
 
61< 0.1%
 
ValueCountFrequency (%) 
-11078228.5%
 
12950.8%
 
21231332.6%
 
3645517.1%
 
4796621.1%
 
ValueCountFrequency (%) 
101< 0.1%
 
61< 0.1%
 
4796621.1%
 
3645517.1%
 
21231332.6%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
0
36780 
1
 
1033
ValueCountFrequency (%) 
03678097.3%
 
110332.7%
 
2020-12-07T06:40:44.445864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
AS_NEW
11598 
UKN
10120 
GOOD
9806 
TO_BE_DONE_UP
2238 
TO_RENOVATE
2029 
Other values (2)
2022 
ValueCountFrequency (%) 
AS_NEW1159830.7%
 
UKN1012026.8%
 
GOOD980625.9%
 
TO_BE_DONE_UP22385.9%
 
TO_RENOVATE20295.4%
 
JUST_RENOVATED19055.0%
 
TO_RESTORE1170.3%
 
2020-12-07T06:40:44.581390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-07T06:40:44.714685image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:44.910409image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length14
Median length4
Mean length5.776452543
Min length3

kitchen
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
0
25033 
1
12780 
ValueCountFrequency (%) 
02503366.2%
 
11278033.8%
 
2020-12-07T06:40:45.036620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

region
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
VLA
23667 
WAL
9538 
BXL
4608 
ValueCountFrequency (%) 
VLA2366762.6%
 
WAL953825.2%
 
BXL460812.2%
 
2020-12-07T06:40:45.176842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-07T06:40:45.311507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:45.454749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

province
Categorical

HIGH CORRELATION

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
VWV
7024 
VAN
5737 
VOV
5043 
BXL
4608 
WHT
4070 
Other values (6)
11331 
ValueCountFrequency (%) 
VWV702418.6%
 
VAN573715.2%
 
VOV504313.3%
 
BXL460812.2%
 
WHT407010.8%
 
VBR397410.5%
 
VLI18895.0%
 
WBR16004.2%
 
WNA14933.9%
 
WLG12723.4%
 
2020-12-07T06:40:45.645674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-07T06:40:45.859904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

sq_m_price
Real number (ℝ≥0)

Distinct16834
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2666.741691
Minimum4.17
Maximum33000
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:46.292553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum4.17
5-th percentile977.78
Q11753.24
median2372.55
Q33105.26
95-th percentile5186.942
Maximum33000
Range32995.83
Interquartile range (IQR)1352.02

Descriptive statistics

Standard deviation1661.788105
Coefficient of variation (CV)0.6231530073
Kurtosis26.85575002
Mean2666.741691
Median Absolute Deviation (MAD)669.41
Skewness3.7751219
Sum100837503.6
Variance2761539.705
MonotocityNot monotonic
2020-12-07T06:40:46.557654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
25002450.6%
 
30001680.4%
 
20001400.4%
 
1666.671000.3%
 
1500910.2%
 
3500850.2%
 
1000830.2%
 
2250740.2%
 
2333.33720.2%
 
2750670.2%
 
Other values (16824)3668897.0%
 
ValueCountFrequency (%) 
4.171< 0.1%
 
10.921< 0.1%
 
15.431< 0.1%
 
30.331< 0.1%
 
42.861< 0.1%
 
ValueCountFrequency (%) 
330001< 0.1%
 
31976.741< 0.1%
 
270001< 0.1%
 
23629.231< 0.1%
 
21739.111< 0.1%
 

sq_m_land_price
Real number (ℝ≥0)

Distinct22878
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1947.327265
Minimum0.75
Maximum33000
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:46.828330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.75
5-th percentile182.35
Q1655.74
median1766.13
Q32663.04
95-th percentile4561.25
Maximum33000
Range32999.25
Interquartile range (IQR)2007.3

Descriptive statistics

Standard deviation1738.105625
Coefficient of variation (CV)0.8925595896
Kurtosis21.1399942
Mean1947.327265
Median Absolute Deviation (MAD)1023.34
Skewness3.065454916
Sum73634285.89
Variance3021011.163
MonotocityNot monotonic
2020-12-07T06:40:47.075023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
25001470.4%
 
3000950.3%
 
2000660.2%
 
1666.67570.2%
 
1500550.1%
 
3500530.1%
 
2333.33480.1%
 
1000430.1%
 
5000420.1%
 
500380.1%
 
Other values (22868)3716998.3%
 
ValueCountFrequency (%) 
0.751< 0.1%
 
1.041< 0.1%
 
1.091< 0.1%
 
1.411< 0.1%
 
2.431< 0.1%
 
ValueCountFrequency (%) 
330001< 0.1%
 
31976.741< 0.1%
 
270001< 0.1%
 
23629.231< 0.1%
 
21739.111< 0.1%
 

type_of_property_num
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
1
20229 
2
17584 
ValueCountFrequency (%) 
12022953.5%
 
21758446.5%
 
2020-12-07T06:40:47.323180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-07T06:40:47.484668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:47.647136image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

subtype_of_property_num
Real number (ℝ≥0)

Distinct21
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.882976754
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:47.882897image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q33
95-th percentile15
Maximum23
Range22
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.285081877
Coefficient of variation (CV)1.103555892
Kurtosis3.705786263
Mean3.882976754
Median Absolute Deviation (MAD)2
Skewness2.07697252
Sum146827
Variance18.36192669
MonotocityNot monotonic
2020-12-07T06:40:48.104060image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
11539940.7%
 
31290634.1%
 
525946.9%
 
1715554.1%
 
913063.5%
 
139702.6%
 
67201.9%
 
74281.1%
 
103200.8%
 
82580.7%
 
Other values (11)13573.6%
 
ValueCountFrequency (%) 
11539940.7%
 
22520.7%
 
31290634.1%
 
4890.2%
 
525946.9%
 
ValueCountFrequency (%) 
23230.1%
 
22570.2%
 
21730.2%
 
20790.2%
 
19620.2%
 

equiped_kitchen_num
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.273160024
Minimum-1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:48.337804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median1
Q33
95-th percentile5
Maximum8
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.972769843
Coefficient of variation (CV)1.549506586
Kurtosis-0.3579932249
Mean1.273160024
Median Absolute Deviation (MAD)2
Skewness0.6007856698
Sum48142
Variance3.891820853
MonotocityNot monotonic
2020-12-07T06:40:48.501781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
11383236.6%
 
-11132429.9%
 
3577815.3%
 
526176.9%
 
219215.1%
 
414363.8%
 
67261.9%
 
71590.4%
 
8200.1%
 
ValueCountFrequency (%) 
-11132429.9%
 
11383236.6%
 
219215.1%
 
3577815.3%
 
414363.8%
 
ValueCountFrequency (%) 
8200.1%
 
71590.4%
 
67261.9%
 
526176.9%
 
414363.8%
 

building_condition_num
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.441435485
Minimum-1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:48.715151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median1
Q33
95-th percentile5
Maximum6
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.852571319
Coefficient of variation (CV)1.285226664
Kurtosis-1.001975372
Mean1.441435485
Median Absolute Deviation (MAD)2
Skewness0.1214234423
Sum54505
Variance3.432020493
MonotocityNot monotonic
2020-12-07T06:40:48.922902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
11159830.7%
 
-11012026.8%
 
3980625.9%
 
422385.9%
 
520295.4%
 
219055.0%
 
61170.3%
 
ValueCountFrequency (%) 
-11012026.8%
 
11159830.7%
 
219055.0%
 
3980625.9%
 
422385.9%
 
ValueCountFrequency (%) 
61170.3%
 
520295.4%
 
422385.9%
 
3980625.9%
 
219055.0%
 

region_num
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size295.4 KiB
1
23667 
2
9538 
0
4608 
ValueCountFrequency (%) 
12366762.6%
 
2953825.2%
 
0460812.2%
 
2020-12-07T06:40:49.146973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-12-07T06:40:49.328190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:49.458140image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

province_num
Real number (ℝ≥0)

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.907835929
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Memory size295.4 KiB
2020-12-07T06:40:49.632585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q37
95-th percentile10
Maximum11
Range10
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.791049227
Coefficient of variation (CV)0.5686924475
Kurtosis-0.7744606279
Mean4.907835929
Median Absolute Deviation (MAD)2
Skewness0.3277874247
Sum185580
Variance7.789955787
MonotocityNot monotonic
2020-12-07T06:40:49.804558image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
6702418.6%
 
2573715.2%
 
5504313.3%
 
1460812.2%
 
8407010.8%
 
3397410.5%
 
418895.0%
 
716004.2%
 
1114933.9%
 
912723.4%
 
ValueCountFrequency (%) 
1460812.2%
 
2573715.2%
 
3397410.5%
 
418895.0%
 
5504313.3%
 
ValueCountFrequency (%) 
1114933.9%
 
1011032.9%
 
912723.4%
 
8407010.8%
 
716004.2%
 

Interactions

2020-12-07T06:39:34.652075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:34.892919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:35.112411image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:35.342866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:35.601986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:35.869847image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:36.128217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:36.363427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:36.601932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:36.876887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:37.113811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:37.399518image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:37.671275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:37.888522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:38.154503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:38.376190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:38.614567image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:38.829570image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:39.045756image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:39.277661image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:39.472691image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:39.722752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:39.942510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:40.172097image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:40.385874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:40.620557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:40.865475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:41.106972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:41.310733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:41.529727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:41.750685image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:41.949996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:42.141693image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:42.332265image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:42.538119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:42.752340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:42.971593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:43.183067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:43.466252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:43.763565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:43.997320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:44.280572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:44.550595image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:44.775610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:44.984686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:45.177633image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:45.403108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:46.577846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:46.822461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:47.065260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:47.278032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:47.505934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:47.737020image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:47.947747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:48.155350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:48.399071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:48.640063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:48.873811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:49.108307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:49.372957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:49.613222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:49.821329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:50.018240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:50.944147image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:51.778325image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:52.034085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:52.330052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:52.578745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:52.894746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:53.200369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:53.641412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:53.918481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:54.118016image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:54.402684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:54.639317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:54.869790image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:55.147393image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:55.371584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:55.650056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:55.923266image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:56.214050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:56.477254image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:56.731989image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:56.997513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:57.216424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:57.461246image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:57.983578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:58.247226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:58.549360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:58.787975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:59.058533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:59.343217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:59.590246image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:39:59.854779image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:00.122527image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:00.380038image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:00.653901image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:00.943373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:01.186224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:01.428568image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:01.676623image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:01.951588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:02.204905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:02.463447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:02.689975image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:02.898145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:03.131297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:03.340064image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:03.545823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:03.773365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:04.077294image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:04.358324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:04.834472image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:05.363827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:05.698600image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:06.198438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:06.542131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:07.026757image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:07.629481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:07.896602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:08.136456image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:08.397354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:08.635267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:08.867993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:09.092329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:09.304089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:09.552918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:09.782384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:10.007977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:10.213899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:10.435496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:10.683112image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:10.904301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:11.125904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:11.366416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:12.410620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:12.674022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:12.900525image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:13.121402image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:13.382929image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:13.593488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:13.809360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:14.031382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:14.252271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:14.504881image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:14.720021image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:14.936285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:15.135441image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:15.335746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:15.599458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:15.809941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:16.035504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:16.232871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:16.453962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:16.689330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:16.925859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:17.173422image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:17.410255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:17.633896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:17.864341image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:18.082175image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:18.304544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:18.589534image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:18.864825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:19.157416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:19.414731image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:19.627911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:19.834678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:20.049383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:20.265607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:20.475521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:20.731842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:20.990789image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:21.228056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:21.440659image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:21.658263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:21.873502image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:22.071259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:22.518952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:23.020226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:23.374737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:23.908416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:24.369077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:24.593439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:24.839725image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:25.042633image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:25.258034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:25.478051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:25.675091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:25.918990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:26.138860image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:26.343311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:26.535695image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:26.777751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:26.979201image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:27.616194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:27.852379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:28.079217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:28.296046image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:28.516438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:28.746061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:28.974217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:29.206315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:29.439561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:29.661548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:29.880598image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:30.107220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:30.312293image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:30.515887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:30.755562image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:30.991929image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:31.232218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:31.449196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:31.644654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:31.881172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:32.074667image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:32.276130image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:32.462464image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:32.663991image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:32.854198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:33.051500image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:33.241942image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:33.430710image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:33.627983image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:33.874458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-12-07T06:40:50.022291image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-12-07T06:40:50.562424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-12-07T06:40:51.182340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-12-07T06:40:51.794852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-12-07T06:40:52.336906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-12-07T06:40:34.452417image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-12-07T06:40:36.444920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

idlocalitytype_of_propertysubtype_of_propertypricenr_of_roomsareaequiped_kitchenopen_fireterraceterrace_areagardengarden_areatotal_land_areanr_of_facadesswimming_poolbuilding_conditionkitchenregionprovincesq_m_pricesq_m_land_pricetype_of_property_numsubtype_of_property_numequiped_kitchen_numbuilding_condition_numregion_numprovince_num
090440811083APARTMENTAPARTMENT265000490INSTALLED01130010340AS_NEW0BXLBXL2944.442572.82111101
190439781000APARTMENTAPARTMENT17950004650USA_HYPER_EQUIPPED1140000105030AS_NEW0BXLBXL2761.541709.52112101
290410954860HOUSEHOUSE3200005231NOT_INSTALLED013011200142130AS_NEW1WALWLG1385.28225.19234129
390430369600APARTMENTAPARTMENT195000275INSTALLED00-1007520GOOD0VLAVOV2600.002600.00111315
490429506010APARTMENTTRIPLEX2350003149HYPER_EQUIPPED01150016420AS_NEW0WALWHT1577.181432.93143128
590420731070APARTMENTAPARTMENT3200003130USA_HYPER_EQUIPPED01140014420AS_NEW0BXLBXL2461.542222.22112101
690422677181HOUSEVILLA3250002130INSTALLED01301600104340TO_BE_DONE_UP0WALWHT2500.00311.60251428
790425115340HOUSEVILLA5690006324INSTALLED015711821220240JUST_RENOVATED0WALWNA1756.17258.402512211
890344941950APARTMENTAPARTMENT7150002126USA_HYPER_EQUIPPED0160013220AS_NEW0VLAVBR5674.605416.67112113
990390191050APARTMENTAPARTMENT15500003213USA_HYPER_EQUIPPED013900252-10AS_NEW0BXLBXL7277.006150.79112101

Last rows

idlocalitytype_of_propertysubtype_of_propertypricenr_of_roomsareaequiped_kitchenopen_fireterraceterrace_areagardengarden_areatotal_land_areanr_of_facadesswimming_poolbuilding_conditionkitchenregionprovincesq_m_pricesq_m_land_pricetype_of_property_numsubtype_of_property_numequiped_kitchen_numbuilding_condition_numregion_numprovince_num
3780390386953000HOUSEHOUSE9400006150UNK00-100150-10UKN1VLAVBR6266.676266.6723-1-113
3780487049371840APARTMENTAPARTMENT3100002102UNK011200114-10UKN1VLAVBR3039.222719.3011-1-113
3780587214131800HOUSEHOUSE4549933169UNK00-1122038930UKN1VLAVBR2692.271169.6523-1-113
3780690629503000APARTMENTFLAT_STUDIO199900026UNK00-1002620UKN1VLAVBR7688.467688.4616-1-113
3780790231871570APARTMENTAPARTMENT215708176UNK0170083-10UKN1VLAVBR2838.262598.8911-1-113
3780890231901570APARTMENTAPARTMENT228208283UNK0170090-10UKN1VLAVBR2749.492535.6411-1-113
3780980660061800APARTMENTAPARTMENT228000186UNK0114134134-10UKN1VLAVBR2651.161701.4911-1-113
3781089665251500APARTMENTAPARTMENT3060003110UNK01500115-10UKN1VLAVBR2781.822660.8711-1-113
3781189665231500APARTMENTAPARTMENT219000165UNK01220087-10UKN1VLAVBR3369.232517.2411-1-113
3781288585901910APARTMENTDUPLEX2750002100UNK011916318220UKN1VLAVBR2750.001510.9919-1-113